A recent article in Harvard Business Review (HBR) (Jan-Feb 2024) by Heimans and Timms discusses the differences between how truth is deciphered in old- and new-power systems. In the old-power system, the article suggests trust is conferred upon the experts; in the new-power system, trust appears to be anchored in the collective wisdom of the crowds. In this analogy, big sample-based research might be likened to a new-power system, drawing upon the collective wisdom of the crowds. Conversely, case-based research could be likened to an old-power system, relying on in-depth analysis of a few cases to reveal the truth. The HBR article also discusses how the advent of AI enables the transition from the new-power system to the Autosapient era. In this era, the pursuit of truth is shifting to the “In AI We Trust” phenomenon, marked by the directed funneling of the truth to the seekers. The Autosapient era increasingly places blind trust in AI systems despite knowing they are black boxes and have every reason not to be right all the time.
I believe there are moments when there is merit in following the AI “truth” or even the wisdom of the crowds, but then, as Einstein said, the truth cannot be decided by the majority alone. In the Autosapeint age driven by AI, as we adapt to novel methods of discerning truth, it is important to acknowledge the significance of case-based research. As the old-power system underscored, truth is often understood by those who have directly experienced it, irrespective of whether the majority subscribes to it – is an entirely distinct narrative.
In sum, as we navigate the Autosapient era, we must not forget to cherish our old-power system – because AI seldom cherishes experts, and without experts, there can be no truth. I hope you enjoy reading the current issue of JITCAR.